How Informative are the Subjective Density Forecasts of Macroeconomists?
AbstractIn this paper, we propose a framework to evaluate the information content of subjective expert density forecasts using micro data from the ECB’s Survey of Professional Forecasters (SPF). A key aspect of our analysis is the use of scoring functions which evaluate the entire predictive densities, including an evaluation of the impact of density features such as their location, spread, skew and tail risk on density forecast performance. Overall, we find considerable heterogeneity in the performance of the surveyed densities at the individual level. Relative to a set of crude benchmark alternatives, this performance is somewhat better for GDP growth than for inflation, although in the former case it diminishes substantially with the forecast horizon. In addition, relative to the proposed benchmarks, we report evidence of some improvement in the performance of expert densities during the recent period of macroeconomic volatility. However, our analysis also reveals clear evidence of overconfidence or neglected risks in the expert probability assessments, as reflected also in frequent occurrences of events which are assigned a zero probability. Moreover, higher moment features of the expert densities, such as their skew or the degree of probability mass in their tails, are shown not to contribute significantly to improvements in individual density forecast performance.
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Bibliographic InfoPaper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 3671.
Date of creation: 2011
Date of revision:
density forecasts; forecast evaluation; real-time data; Survey of Professional Forecasters;
Other versions of this item:
- Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2012. "How informative are the subjective density forecasts of macroeconomists?," Working Paper Series 1446, European Central Bank.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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